QA Lead Engineer (AI-First Engineering Organization)

Finite State

2h•$120,000 - $160,000•Remote

About The Position

We are seeking an experienced QA Lead Engineer to drive quality strategy and execution within an AI-first development organization. This is not a traditional QA lead role — we are looking for a hands-on technical leader who can architect and implement an automated, AI-first quality framework that scales with modern software development. In our environment, AI is a first-class partner in software creation. The QA Lead Engineer will define how quality is engineered into the product using automation, AI agents, and deep collaboration with Product and Engineering. If you have over a decade of QA automation experience and are excited about redefining what quality means in an AI-native development lifecycle, we want to talk to you.

Requirements

10+ years of experience in QA engineering, with deep expertise in automation.
Demonstrated thought leadership and hands on implementation experience with creating AI-driven Agentic quality systems.
Proven experience designing and implementing automated test frameworks at scale.
Strong programming skills (e.g., Python, JavaScript/TypeScript, Java, or similar).
Experience with Cloud based CI/CD systems and modern DevOps practices.
Demonstrated technical leadership in cross-functional teams.
Experience using AI tools and agents in development workflows.
Deep experience with AI Agents and LLMs and how to test AI-driven systems.
Strong communication skills with the ability to influence Product and Engineering leaders.
Experience driving process improvements across teams.
Ability to operate strategically while remaining hands-on.
A mindset focused on systems thinking, scalability, and continuous improvement.

Nice To Haves

Experience with autonomous test generation or AI-assisted test maintenance is highly desirable.
Understanding of challenges specific to testing AI systems (non-determinism, hallucination, evaluation frameworks).

Responsibilities

Define and own the end-to-end QA strategy for an AI-first engineering team.
Architect scalable, fully automated testing frameworks across backend, frontend, APIs, and AI-powered features.
Lead the transition from traditional QA practices to AI-driven quality engineering.
Establish quality metrics, SLAs, and measurable standards across the product lifecycle.
Serve as the technical authority on testing architecture, tooling, and best practices.
Design and implement AI-agent-driven QA workflows (e.g., autonomous test generation, regression validation, autonomous testing agents).
Integrate LLM-based or AI-assisted tooling into CI/CD pipelines.
Leverage AI to improve test coverage, defect detection, root cause analysis, and release confidence.
Evaluate and introduce emerging AI QA tooling and frameworks.
Develop strategies for testing AI-based product features (e.g., model behavior validation, output consistency, guardrail enforcement).
Partner closely with Product to define acceptance criteria, quality gates, and risk assessments.
Work with Engineering leadership to embed quality earlier in the development lifecycle.
Drive a culture where developers co-own quality and automation.
Lead post-incident quality reviews and implement systemic improvements.
Define and standardize quality processes across squads.
Leverage AI to build autonomous QA systems that understand the context of product decisions, and use that context to drive the highest quality
Build frameworks and reusable testing infrastructure.
Mentor engineers on best practices in automation and AI-driven testing.